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Record W4386775947 · doi:10.53379/cjcd.2023.381

Fostering graduate student engagement for the future of career development

2023· article· en· W4386775947 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Career Development · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsMentorshipStudent engagementGraduate studentsConstructiveCareer developmentCommunity engagementWork (physics)PedagogyMedical educationSociologyEngineering ethicsPublic relationsPsychologyPolitical scienceEngineeringMedicineProcess (computing)Computer science

Abstract

fetched live from OpenAlex

This article addresses the challenges faced by graduate students throughout their academic journeys and highlights the pivotal role of organizations such as CERIC in enriching their experiences through active engagement, mentorship, and fostering a sense of connection and belonging. It emphasizes the significance of engagement programs, specifically focusing on the Graduate Student Engagement Program (GSEP). The GSEP offers valuable opportunities for graduate students to connect with peers and experts in their field, fostering an environment conducive to sharing experiences, exchanging knowledge, and building professional networks. GSEP serves as a platform for graduate students to showcase their work and research outcomes, receive constructive feedback, and actively contribute to a vibrant community of scholars. By acknowledging and supporting the unique needs of graduate students, organizations and engagement programs play a vital role in empowering the next generation of researchers and practitioners in career development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.193
GPT teacher head0.334
Teacher spread0.141 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it